Signal-aware deep learning–based respiratory motion prediction for lung tumor management

This study focuses on algorithmic feasibility and establishes a computational foundation for future clinically calibrated and dosimetrically validated models. The findings indicate that the proposed approach can support future motion-aware radiotherapy planning strategies by improving motion characterization at the algorithmic level.

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Publication Details

Journal
Frontiers in Oncology
Published
2026-02-13
DOI
https://doi.org/10.3389/fonc.2026.1735140
Primary Topic
Advanced Radiotherapy Techniques
Type
article
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article

Signal-aware deep learning–based respiratory motion prediction for lung tumor management

Karobi Das, Partha Pratim MEdhi, Dr Chandra J
Frontiers in Oncology
Advanced Radiotherapy Techniques
article

Signal-aware deep learning–based respiratory motion prediction for lung tumor management

Karobi Das, Partha Pratim MEdhi, Dr Chandra J
article en

Abstract

This study focuses on algorithmic feasibility and establishes a computational foundation for future clinically calibrated and dosimetrically validated models. The findings indicate that the proposed approach can support future motion-aware radiotherapy planning strategies by improving motion characterization at the algorithmic level.

Frontiers in OncologyVol. 16
Concordia University Irvine (US), Christ University (IN), All India Institute of Medical Sciences (IN)
Good health and well-being
Openalex Percentile: Top 52%
Advanced Radiotherapy Techniques
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